This application is in the area of Chemical Biology (Area 2). Glycosylation,[unreadable] which creates a diverse array of carbohydrate epitopes attached to cell surface[unreadable] proteins and lipids, is an inherently complex system that is poorly understood.[unreadable] Carbohydrates play crucial roles in a diverse array of medically relevant[unreadable] biological processes from viral pathogenesis to tumor cell metastasis and stem[unreadable] cell differentiation. However, due to the biosynthetic and molecular complexity of[unreadable] these biopolymers, we have little comprehension of how glycan synthesis is[unreadable] controlled. Systems-based approaches to biology, in which large datasets are[unreadable] analyzed using bioinformatic algorithms, provide an important avenue for[unreadable] exploring the mechanics of complex systems that cannot be predicted a-priori.[unreadable] Application of such approaches to glycosylation however has been limited due to[unreadable] the lack of methodology for high-throughput analysis of carbohydrates[unreadable] (glycomics). Recent work in my laboratory on lectin microarray technology has[unreadable] begun to address the analytical problems inherent in glycomics and thus pave[unreadable] the way for systematic analysis of the glycome. I propose to use the NCI-60 cell[unreadable] panel as a model system to integrate glycomic information with proteomic,[unreadable] genomic and metabolic pertubation data to create a predictive model of how cell[unreadable] surface glycosylation is encoded. To achieve this objective, we will reinvent[unreadable] bioinformatics technology for glycomics including analytical and databasing[unreadable] methods, integration of information and predictive modeling, providing useful[unreadable] tools for the study of glycomics in a wide variety of contexts. Detailed knowledge[unreadable] of how the genome and other factors control glycosylation will have a strong[unreadable] impact on a diverse swath of fields where carbohydrates play important roles[unreadable] including immunology, cancer research and developmental biology and may[unreadable] impact their use as potential biomarkers for disease.